35 parallel-computing-numerical-methods-"Prof" Postdoctoral positions at University of London
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About the Role A fully funded Postdoctoral Research Associate position is available to join a team led by Prof Susana Godinho to study the role of microtubule alterations in normal physiology and
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will compare the development of annelids and molluscs and combine single-cell transcriptomics with classic embryological approaches and state-of-the-art computational methods. The findings from
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project investigating mechanosensing in Diptera. This post will focus on using detailed wing geometry models and kinematic measurements in computational fluid and structural dynamics simulations to recover
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. Research will focus on identifying and publishing results in methods to build foundation models, using multimodal and multiscale health data. The role is funded for 24 months in the first instance. About You
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About the Role We are seeking a researcher for a new programme focused on improving understanding of cancer risk and developing novel multicancer risk prediction models to support cancer prevention
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developmental science. The successful candidate will contribute to a major research programme investigating how educational experiences shape mental health from childhood into adulthood. The role involves working
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related to gravitational wave astronomy. The primary aim will be the development of advanced approaches for computational Bayesian Inference to measure the properties of Compact Binary Coalescence signals
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to someone proactive and ambitious who has obtained their PhD and has begun an academic career in epidemiology, pharmacoepidemiology, or medical statistics, with a focus on causal inference methods applied
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Research Council’s (AHRC) Bridging Responsibilities AI Divides (BRAID) programme that will explore new technologies, new business models and new approaches to data provenance in pursuit of an equitable
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science. About You We are seeking a PDRA who will use advanced statistical and computational methods to analyse multi-omics datasets, such as genomics, proteomics, and metabolomics. You will develop